In the semiconductor industry, devices are fabricated by a number of manufacturing processes producing structures of an ever-decreasing size. Thus, such processes as inspection, metrology and alike (referred to hereinafter as inspection processes) require increased precision and effectiveness for manufacturing specimens. The term “specimen” used in this specification should be expansively construed to cover any kind of wafer, reticle and other structures, combinations and/or parts thereof used for manufacturing semiconductor integrated circuits, magnetic heads, flat panel displays, and other thin film devices.
Inspection processes can include recognition of structural elements, measuring, calibration, monitoring, inspection, reporting and/or other procedures necessary for evaluating parameters and/or conditions of respective manufacturing processes and providing necessary feedback. A variety of inspection tools can be based on non-destructive observations as, by way of non-limiting example, scanning electron microscopes, atomic force microscopes, optical inspection tools, etc. Inspection processes are important for debugging specimen manufacturing processes, monitoring process variations, improving production yield, etc.
With shrinking design rules (28 nm and below), the amount of defect-related data reported by a high-sensitivity inspection tools is extremely large (e.g. several thousand defects per wafer). In addition, adoption of new manufacturing processes (e.g. immersion lithography, resist shrinking, resist trimming, etc.) introduces new types of errors resulting from different proximity effects (optical, CMP, chemical, 3D, etc.) and reported by inspection tools as defects. The severities of reported defects can vary from disastrous impacts on product yields to trivial anomalies with no effect on product quality.
Thus, there is a need to classify the reported defects and to separate defects of interest (DOI) from defects that are considered nuisances. As manufacture control requirements become more challenging, classification of reported defects has also become highly complex and time and processing power consuming.
Problems of classifying defects during a fabrication process have been recognized in the conventional art and various techniques have been developed to provide solutions.
One of the typical approaches is analyzing predefined attributes of the defect (e.g. size, magnitude, orientation, shape, etc.) and performing classification based on these attributes. Other classification techniques consider also positioning of the reported defects in the specimen (e.g. with regard to certain defined regions).
The defects can be classified based on one or more attributes of the defect and one or more attributes of the one or more patterned features formed on the specimen proximate to the defect. In such a manner, the defects can be classified based not only on the attribute(s) of the defects, but also on the attribute(s) of any patterned features located on the specimen proximate to the defect.
The defects can be further classified using various methods for utilizing design data in combination with inspection data.